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Numerical Modeling of Unstable Water Floods and Tertiary Polymer Floods into Highly Viscous Oils

机译:不稳定水洪水和三级聚合物洪水中的数值模拟成高粘性油

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The saturation distribution after unstable water flooding into highly viscous oil may have a decisive impact on the efficiency of tertiary polymer flooding, in particular due to hysteresis effects associated with oil banking. In this work, we model water flood and tertiary polymer flood experiments performed on Bentheimer sandstone slabs with heavy oils of about 2000 cP and 7000 cP, and compare the numerical results with experimental production, pressure and X-ray data. The unstable water floods are initially simulated in 2D with our parallel in-house research reservoir simulator using a high-resolution discretization. In agreement with existing literature, we find that Darcy- type simulations based on steady-state relative permeabilities - inferred here from a 3D quasistatic pore network model (PNM) - cannot predict the measured water flood data. Even qualitatively, the viscous fingering patterns are not reproduced. An adaptive dynamic pore network model is then applied on a 2D pore network constructed from the statistics of the 3D network. If the fingering patterns simulated with this 2D PNM are qualitatively in good agreement with the experimental data, a quantitative match cannot be obtained due to the limitations of 2D modeling. Although 3D dynamic PNM at the slab scale would currently lead to prohibitively high computational cost, it has the potential to address the deficiencies of continuum models at highly unfavorable viscosity ratio. For the tertiary polymer floods characterized by a much more favorable mobility ratio, Darcy-type modeling is applied and history matching is conducted from the end of the water floods. We find that unless hysteresis due to oil banking is accounted for in the relative permeability model, it is not possible to reconcile the experimental data sets. This hysteresis phenomenon, associated with oil invasion into previously established water channels, explains the rapid propagation of the oil bank. For the considered experiments, a simultaneous history match of good quality is obtained with the production and pressure data, and the simulated 2D saturation maps are in reasonable agreement with X-ray data. This paper addresses the challenges in modeling highly unstable water flooding, using both a conventional Darcy-type simulator and adaptive dynamic PNM, by confronting the simulated results with experimental data including saturation maps. It also highlights the important role of relative permeability hysteresis in the tertiary recovery of viscous oils by polymer injection.
机译:在不稳定的水中浸入高粘度油后的饱和分布可能对叔聚合物泛滥的效率产生决定性影响,特别是由于与油库相关的滞后效应。在这项工作中,我们模拟了在Bentheimer砂岩板上进行的水洪水和三级聚合物洪水实验,其具有大约2000cp和7000cp的重油,并比较实验生产,压力和X射线数据的数值结果。使用高分辨率离散化,最初在2D中模拟了不稳定的水洪水,其平行的内部研究储层模拟器。在现有文献方面,我们发现基于稳态相对渗透率的达西型模拟 - 从3D Quasistatic Pore网络模型(PNM)推断出 - 无法预测测量的水洪水数据。甚至定性地,粘性指法图案也不会被复制。然后对由3D网络统计构成的2D孔隙网络应用自适应动态孔网络模型。如果使用该2D PNM模拟的指向图案与实验数据良好的吻合,则由于2D造型的限制,不能获得定量匹配。尽管平板刻度的3D动态PNM当前导致计算成本高,但它有可能以极其不利的粘度比解决连续模型的缺陷。对于特征在于具有更有利的迁移率的三级聚合物泛洪,应用达西型建模和历史匹配从水洪水结束进行。我们发现,除非在相对渗透性模型中占据了由于油库导致的滞后,否则不可能协调实验数据集。这种滞后现象与油侵入进入以前建立的水通道,解释了石油银行的快速繁殖。对于考虑的实验,利用生产和压力数据获得良好质量的同时历史匹配,并且模拟的2D饱和图与X射线数据合理一致。本文通过将模拟结果与包括饱和图在内的实验数据构成模拟结果,解决了使用传统的达西型模拟器和自适应动态PNM来建立高度不稳定的水洪水的挑战。它还强调了相对渗透率滞后在聚合物注射液中相对渗透率滞后的重要作用。

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